Abstract
Background
Trends in cardiovascular disease (CVD) mortality from key risk factors both in the United States (US) and globally have not been well characterized.
Methods
This analysis utilized Global Burden of Disease (GBD) 2019 data to determine age-standardized mortality rates (ASMR) and disability-adjusted life years (DALYs) for CVDs attributed to risk factors in the US and globally. Total percentage change (TPC, 95 % CI) was calculated to assess temporal trends in CVD mortality and disease burden related to key risk factors, examining two periods: 1990–2010 and 2010–2019.
Results
Overall CVD mortality declined in the US and globally from 1990–2019. CVD mortality declined globally by a TPC of -0.24 (-0.26 to -0.22) between 1990–2010 but only by -0.11 (-0.15 to -0.07) between 2010–2019. Similar changes were seen in the US. CVD mortality attributed to common risk factors, including dietary risks, high LDL-c, kidney dysfunction, smoking, and secondhand smoking, changed significantly between 2010–2019 compared to the prior two decades, with slower declines in CVD mortality both globally and in the US. Furthermore, CVD mortality attributed to high body mass index, elevated fasting plasma glucose, and elevated systolic blood pressure in the US plateaued from 2010–2019. Trends in DALYs attributed to these risk factors paralleled those observed for mortality.
Conclusions
Despite major reductions in CVD mortality and disease burden from 1990 to 2010, mortality linked to key risk factors plateaued globally and in the US after 2010. Continued public health efforts targeting key risk factors are needed to further reduce CVD-related mortality and disability.
Keywords: Cardiovascular mortality, Risk factors, Obesity, High blood pressure, Fasting plasma glucose, Diet
1. Introduction
Cardiovascular disease (CVD) is the leading cause of mortality worldwide despite advancements in medical treatments, in public health policies and interventions, and in access to care. Country-level data including in the United States (US) has demonstrated that the declines in CVD mortality seen over the prior decade have slowed in the 2010s [1,2]. Slowing improvements in CVD mortality have been attributed to several factors, including rising prevalence of CVD risk factors. Increases in burden of CVD risk factors including obesity and hyperglycemia have been observed globally, and similar trends have occurred in countries including the US [3,4]. However, the global and US trends in CVD mortality attributed to key CVD risk factors have not been well characterized. Particularly, evaluation of CVD mortality attributed to common cardiovascular risk factors is important both as a way to potentially pinpoint contributors to the slowing improvements in CVD mortality as well as to focus public health efforts to optimize CVD health. Therefore, we examined the 2019 Global Burden of Disease (GBD) data to characterize the rates and trends in CVD mortality attributed to common risk factors both in the US and globally.
2. Methods
This study is based on data from the GBD 2019, which spans from 1990 to 2019. Data on age-standardized mortality rates (ASMR per 100,000 individuals with 95 % uncertainty intervals) and disability-adjusted life years (DALYs per 100,000 individuals) from CVD and CVD attributable to cardiovascular risk factors was obtained from the Global Health Data Exchange https://ghdx.healthdata.org/gbd-2019. Global and US data were obtained. Eight attributable risk factors as defined within the GBD were evaluated, including: dietary risks, high body mass index (BMI), high fasting plasma glucose, high low-density lipoprotein cholesterol (LDL-c), high systolic blood pressure (SBP), kidney dysfunction, low physical activity, smoking, and secondhand smoke. This study used publicly available, anonymized, and aggregated GBD data; the study was exempt from institutional review board approval and informed consent was not required.
To assess the temporal trends of age-standardized CVD burden from 1990 to 2019, the total percent change (TPC) with 95 % confidence intervals (CI) were used to evaluate changes in CVD ASMR in the US and globally. TPC was analyzed in two time segments as possible within the GBD: 1990 to 2010 and 2010 to 2019. A positive TPC indicates a growing burden of disease, while a negative TPC signifies a decline in disease burden. Values that do not cross 0 imply statistically significant trends.
3. Results
Between 1990 and 2019, the global ASMR from overall CVD declined from 354.5 (330.6 to 369.5) to 239.9 (219.4 to 254.9), with TPC −0.24 (−0.26 to −0.22) between 1990–2010 slowing to a TPC −0.11 (−0.15 to −0.07) between 2010–2019. Corresponding data for the US are also shown in Table 1.
Table 1.
Total percent change (TPC) of age-standardized mortality rates (ASMRs) due to cardiovascular disease overall and cardiovascular disease attributable to common risk factors: a comparison of United States and global trends from 1990 to 2019.
| ASMR per 100k (1990) |
ASMR per 100k (2010) |
ASMR per 100k (2019) |
ASMR TPC (1990–2010) |
ASMR TPC (2010–2019) |
|
|---|---|---|---|---|---|
| United States | 264.6 (245.1 to 274.1)* | 162.9 (148.5 to 170.7)* | 157.0 (141.7 to 165.1)* | −0.38 (−0.40 to −0.37) | −0.04 (−0.05 to −0.02) |
| Risk attributable deaths where decline has plateaued | |||||
| High BMI | 50.8 (29.8 to 74.1) | 39.6 (26.0 to 53.5) | 39.0 (25.5 to 52.4) | −0.22 (−0.29 to −0.09) | −0.01 (−0.04 to 0.02) |
| High FPG | 51.9 (34.8 to 75.2) | 41.5 (27.1 to 61.6) | 40.4 (26.6 to 59.7) | −0.20 (−0.29 to −0.08) | −0.03 (−0.08 to 0.02) |
| High SBP | 144.0 (120.8 to 164.3) | 72.5 (59.6 to 85.4) | 70.3 (58.0 to 82.6) | −0.50 (−0.53 to −0.46) | −0.03 (−0.09 to 0.03) |
| Risk attributable deaths where decline has slowed | |||||
| Dietary risks | 107.1 (86.5 to 126.1) | 70.0 (49.4 to 73.6) | 57.6 (46.5 to 69.8) | −0.43 (−0.46 to −0.40) | −0.06 (−0.08 to −0.04) |
| High LDL-c | 108.2 (83.4 to 134.4) | 42.5 (31.3 to 55.3) | 38.0 (27.7 to 50.0) | −0.61 (−0.64 to −0.57) | −0.11 (−0.13 to −0.09) |
| Kidney dysfunction | 31.0 (23.4 to 39.2) | 17.6 (13.1 to 22.3) | 17.1 (12.8 to 21.4) | −0.43 (−0.45 to −0.40) | −0.03 (−0.06 to −0.01) |
| Low physical activity | 11.0 (3.4 to 23.2) | 6.3 (2.3 to 12.8) | 4.3 (1.3 to 9.8) | −0.43 (−0.23 to −0.53) | −0.32 (−0.19 to −0.49) |
| Secondhand smoke | 7.1 (5.9 to 8.4) | 2.7 (2.3 to 3.2) | 2.6 (2.1 to 3.0) | −0.62 (−0.64 to −0.59) | −0.06 (−0.12 to −0.01) |
| Smoking | 68.2 (64.8 to 71.7) | 30.1 (28.2 to 32.0) | 25.8 (24.1 to 27.6) | −0.56 (−0.58 to −0.53) | −0.14 (−0.17 to −0.11) |
| Global | 354.5 (330.6 to 369.5)* | 269.9 (250.6 to 280.9)* | 239.9 (219.4 to 254.9)* | −0.24 (−0.26 to −0.22) | −0.11 (−0.15 to −0.07) |
| Risk attributable deaths where decline has plateaued/remained stable | |||||
| High BMI | 43.3 (23.1 to 68.8) | 40.8 (24.2 to 60.6) | 40.1 (24.7 to 58.5) | −0.06 (−0.13 to 0.06) | −0.02 (−0.07 to 0.05) |
| High FPG | 52.7 (36.1 to 77.1) | 51.2 (35.2 to 75.2) | 48.4 (33.1 to 70.4) | −0.03 (−0.08 to 0.03) | −0.05 (−0.10 to 0.00) |
| Risk attributable deaths where decline has slowed | |||||
| Dietary risks | 138.5 (114.4 to 166.2) | 99.6 (80.6 to 121.8) | 87.4 (70.6 to 107.4) | −0.28 (−0.31 to −0.25) | −0.12 (−0.17 to −0.08) |
| High LDL-c | 89.3 (67.1 to 115.6) | 63.2 (47.2 to 81.9) | 56.5 (41.8 to 73.6) | −0.29 (−0.31 to −0.27) | −0.11 (−0.15 to −0.06) |
| High SBP | 188.2 (165.9 to 210.9) | 143.4 (125.6 to 161.2) | 127.5 (110.6 to 143.8) | −0.24 (−0.27 to −0.21) | −0.11 (−0.16 to −0.06) |
| Kidney dysfunction | 29.0 (21.8 to 36.2) | 24.5 (18.7 to 30.6) | 22.4 (16.9 to 28.0) | −0.16 (−0.19 to −0.13) | −0.09 (−0.13 to −0.05) |
| Low physical activity | 12.6 (5.1 to 24.2) | 9.6 (4.1 to 18.2) | 8.6 (3.7 to 16.3) | −0.23 (−0.16 to −0.28) | −0.11 (−0.06 to −0.16) |
| Secondhand smoke | 11.5 (9.5 to 13.4) | 8.4 (6.9 to 9.9) | 7.4 (6.1 to 8.9) | −0.27 (−0.30 to −0.23) | −0.11 (−0.17 to −0.06) |
| Smoking | 57.2 (54.5 to 60.0) | 39.9 (37.8 to 41.9) | 33.0 (30.4 to 35.5) | −0.30 (−0.33 to −0.27) | −0.17 (−0.23 to −0.11) |
Data is presented as ASMR with 95 % UI. CVD: cardiovascular deaths; TPC: total percent change; ASMR: age-standardized mortality rate; BMI: body mass index; FPG: fasting plasma glucose; LDL-c: low-density lipoprotein cholesterol; SBP: systolic blood pressure; UI: 95 % uncertainty interval. Bolded values indicate both 95 % Cis 〈 0 or 〉 0, Italicized values include 0 as one of the 95 % Cis. *Overall CVD mortality irrespective of attributable cause.
The ASMRs CVD attributed to the studied risk factors both globally and in the US are shown in Table 1. In 2019, the highest CVD ASMRs for attributable risk factors globally were from high SBP (127.5, 110.6 to 143.8) and dietary risks (87.4, 70.6 to 107.4). Similarly, the highest CVD ASMRs for attributable risk factors in the US were from high SBP (70.3, 58.0 to 82.6) and dietary risks (57.6, 46.5 to 69.8).
The mortality trends both globally and in the US for CVD mortality attributed to the studied risk factors are also shown in Table 1 and Fig. 1. Between 1990–2010, globally, there was a decline in most risk-attributable CVD mortality except for CVD mortality attributable to high BMI (TPC −0.06, −0.13 to 0.06) and fasting plasma glucose (TPC −0.03, −0.08 to 0.03). Between 1990 and 2010, there was a decline in all risk factor attributable CVD mortality in the US. However, there were prominent differences both globally and in the US when the TPC trends were compared between the 1990–2010 and the 2010–2019 time periods, as shown in Table 1. For most of the studied risk factors, the decline in CVD mortality attributed to that risk was smaller between 2010–2019 compared to the decline noted between 1990–2010, with some risk factors demonstrating that the declines noted between 1990–2010 have plateaued between 2010–2019.
Fig. 1.
Age-standardized mortality rates (ASMRs) per 100,000 from 1990 to 2019 for cardiovascular disease (CVD) mortality attributed to nine risk factors. Each panel shows trends in CVD mortality attributable to a specific modifiable risk factor: (A) Dietary risks, (B) High body mass index, (C) High fasting plasma glucose, (D) High LDL cholesterol, (E) High systolic blood pressure, (F) Kidney dysfunction, (G) Low physical activity, (H) Secondhand smoke, and (I) Smoking. Purple lines represent global ASMRs per 100,000 for both sexes, while green lines represent United States data for both sexes. Shaded areas around each line denote 95 % uncertainty interval.
3.1. Attributable risk factors for CVD mortality where the decline plateaued or remained stable
In the US, CVD mortality attributable to high BMI declined from 1990–2010 (TPC −0.22, −0.29 to −0.09), but this decline plateaued after 2010 (TPC −0.01, −0.04 to 0.02). Globally, the ASMR for CVD mortality attributable to high BMI remained stable, with stable TPC between 1990–2010 (−0.06, −0.13 to 0.06) and 2010–2019 (0.02, −0.07 to 0.05). Similarly, US CVD mortality attributable to high fasting plasma glucose declined from 1990–2010 (TPC −0.20, −0.29 to −0.08), but then plateaued after 2010 (TPC of −0.03, −0.08 to 0.02). Globally, for CVD mortality attributable to high fasting plasma glucose, the ASMR was stable from 1990–2010 (−0.03, −0.08 to 0.03), there was trend towards decline from 2010–2019 (TPC −0.05, −0.10 to 0.00).
For other risk factors, such as high SBP, the decline in ASMR slowed globally with a less prominent decline between 2010–2019 (TPC −0.11, −0.16 to −0.06) compared to 1990–2010 (TPC −0.24, −0.27 to −0.21). In the US, the decline in ASMR for CVD mortality attributed to high SBP plateaued in the US between 2010–2019 (TPC −0.03, −0.09 to 0.03) after falling from 1990–2010 (−0.50, −0.53 to −0.46).
3.2. Attributable risk factors for CVD mortality where the decline slowed
Globally, the TPC for CVD mortality attributed to risk factors slowed significantly between 2010–2019 compared to 1990–2010 for dietary risk (TPC −0.12, −0.17 to −0.08 vs −0.28, −0.31 to −0.25), high LDL-c (TPC −0.11, −0.15 to −0.06 vs −0.29, −0.31 to −0.27), kidney dysfunction (TPC −0.09, −0.13 to −0.05 vs −0.16, −0.19 to −0.13), low physical activity (TPC −0.11, −0.06 to −0.16 vs −0.23, −0.16 to −0.28), smoking (TPC −0.11, −0.17 to −0.06 vs −0.27, −0.30 to −0.23), and secondhand smoke (TPC −0.17, −0.23 to −0.11 vs −0.30, −0.33 to −0.27). Similar trends were seen in the US for risk factors.
3.3. Attributable risk factors for DALYs mirrored mortality trends
Trends in age-standardized DALYs attributable to the same nine cardiovascular risk factors were largely consistent with the mortality trends (Fig. 2).
Fig. 2.
Age-standardized disability-adjusted life years (DALYs) per 100,000 from 1990 to 2019 for cardiovascular disease (CVD) attributed to nine risk factors. Each panel shows trends in CVD DALYs attributable to a specific modifiable risk factor: (A) Dietary risks, (B) High body mass index, (C) High fasting plasma glucose, (D) High LDL cholesterol, (E) High systolic blood pressure, (F) Kidney dysfunction, (G) Low physical activity, (H) Secondhand smoke, and (I) Smoking. Purple lines represent global DALYs per 100,000 for both sexes, while green lines represent United States data for both sexes. Shaded areas around each line denote 95 % uncertainty interval.
4. Discussion
This analysis of CVD mortality attributable to common cardiovascular risks globally and in the US demonstrates several important findings. Although overall CVD ASMRs have declined between 1990 and 2019 both globally and in the US, the declines have slowed between 2010 and 2019. CVD mortality attributed to common cardiovascular risk factors has also significantly changed between 2010 and 2019 compared to the prior two decades, with slower declines in CVD mortality attributed to dietary risks, high LDL-c, kidney dysfunction, smoking and secondhand smoking both globally and in US. Furthermore, there has been a plateau of CVD mortality attributed to high BMI, elevated fasting plasma glucose, and elevated SBP in the US from 2010–2019. These findings highlight the ongoing burden of common risk factors as potential reasons for attenuation of prior declines in CVD mortality both globally and in the US and may help to increase public health awareness of the role of common risk factors on CVD mortality.
Our study expands on the prior literature regarding risk factor and CVD mortality. Metabolic risk factors, including hypertension, hyperlipidemia, diabetes, poor diet, and others are well known contributors to CVD and most CVD mortality is attributable to these potentially modifiable risk factors, both in North America and globally [5,6]. Prior studies from the GBD identified dietary risks, elevated SBP and LDL-c, smoking, high BMI and elevated fasting plasma glucose as the important contributors to ischemic heart disease mortality [[7], [8], [9]]. However, there are less data available regarding the trends in CVD mortality attributable to common risk factors, particularly in the US [10]. Using data from a large cohort from the Rotterdam study in the Netherlands, the authors noted a decrease in six modifiable CVD risk factors between the 1990s and 2010s, although the contribution of obesity and dyslipidemia increased in the last decade of the study [11]. Prior analyses from the GBD have highlighted declines in CVD mortality attributable to metabolic risk factors, but did not expand on important trend differences in the latter portion of the study period [12,13]. Our results complement this prior literature with additional data not only on CVD deaths attributable to individual risk factors but also their trends both globally and in the US, with specific evaluation of CVD mortality data over the last decade. Additionally, our findings revealed consistent patterns in CVD-related DALYs, demonstrating disease burden beyond mortality.
In the US and globally, declines in CVD mortality between 1990 and 2019 attributed to metabolic risk factors may be related to changes in the prevalence and severity of metabolic risk factors during that time [3,14]. Declines in modifiable risk factor burden including hypertension and hyperlipidemia may be related to the introduction of effective lipid lowering agents and greater global awareness of the importance of treatment. On the other hand, the prevalence of obesity has continued to increase both in the US and globally, which may attenuate the declines in CVD mortality both related to obesity itself and to other concomitant risk factors involved in metabolic syndrome or the newly described cardiovascular-kidney-metabolic (CKM) syndrome [15]. Although global declines of CVD mortality related to metabolic risk factors between 1990–2017 have been more prominent in regions with higher socio-demographic index [16], our finding show that, specifically for the US, greater CVD mortality declines between 1990–2010 compared to global rates have been attenuated and declines between 2010–2019 now lag global rates. Etiologies of these trends will require further evaluation, particularly regarding slowing mortality benefits in the US relative to worldwide trends.
These results have important clinical implications for global efforts to combat CVD mortality. Although increased public health efforts aimed at modification of key risk factors such as smoking [17] have been successful at reducing the burden of CVD attributed to specific risk factors, our results show that much work remains to address other modifiable risk factors both in the US and globally. Specifically, additional efforts will be needed to optimize modifiable risk factors, particularly those with increasing prevalence and contribution to CVD mortality such as obesity [18]. In the US, optimizing risk factors will be reliant on greater emphasis on prevention-oriented primary care, integration of cardiometabolic management and the CKM framework into routine clinical workflows, and stronger alignment of reimbursement models with long-term risk reduction. Clinical systems could prioritize population-level risk stratification, early intervention for metabolic conditions, and multidisciplinary care models that reflect the complexity and overlap of CVD risk factors. Additionally, current efforts to combat obesity and related CVD risks may focus on novel weight loss therapies (such as Glucagon-Like Peptide-1 agonists); the effects of these novel therapies on long term CVD outcomes on the population level will require future evaluation. Further efforts will also be needed to address social determinants of health, which play a key role in control of CVD risk factors [19]. Similar efforts will also be needed globally, particularly in regions with less access to novel therapies for metabolic conditions and regions with less socio-economic development which have previously experienced slower improvement in CVD health [16,20].
5. Limitations
Our analysis has limitations. The data were obtained from a large multinational dataset, which uses a variety of data and data modeling to present results. Not all potential risk factors for CVD mortality available within the GBD were reported, although we described the risk factors which are commonly attributed to CVD mortality. Overall, CVD attributable to risk factors within the GBD did not include all the CVD categories for every individual risk factor. We did not report the impact of risk factors on individual causes of CVD mortality, which may be important as the contribution of risk factors may vary for different individual components of CVD. Worldwide data included US data, which would serve to narrow the reported differences between US and global ex-US trends. The time intervals, including the use of the year 2010 to determine the two periods, were evaluated as available within the GBD. Nevertheless, the GBD is a commonly used data source, including for reporting longitudinal country-specific and global trends in public health outcomes.
6. Conclusion
In conclusion, we present global and US trends on CVD mortality attributable to important risk factors such as obesity, elevated SBP and blood sugar, and dietary risks among others. While significant reductions in CVD mortality were achieved between 1990 and 2010, the slowing rates of improvement or rate plateau among CVD mortality attributed to key risk factors were observed after 2010. These findings underscore the complexity of the efforts of the last decade to addressing risk factors such as obesity, diabetes, hypertension, and diet. Comprehensive public health strategies and healthcare interventions are needed to sustain and re-accelerate progress in reducing CVD burden both globally and in the US, particularly as the prevalence of metabolic disorders continues to rise.
Funding
None
Disclosures
Dmitry Abramov has received speaker fees from Bayer and AstraZeneca. Michael D. Shapiro has participated in scientific advisory boards with the following entities: Amgen, Agepha, Ionis, Novartis, Precision BioScience, Novo Nordisk; and has served as a consultant for Ionis, Novartis, Regeneron, EmendoBio, Aidoc, and Shanghai Pharma Biotherapeutics. All other authors have nothing to disclose.
CRediT authorship contribution statement
George W. Hafzalla: Writing – review & editing, Writing – original draft, Visualization. Dmitry Abramov: Writing – review & editing, Supervision, Resources. Michael D. Shapiro: Writing – review & editing. Abdul Mannan Khan Minhas: Writing – review & editing, Resources, Methodology, Investigation, Formal analysis, Conceptualization.
Declaration of competing interest
Dmitry Abramov reports a relationship with Bayer that includes: speaking and lecture fees. Dmitry Abramov reports a relationship with AstraZeneca that includes: speaking and lecture fees. Michael D. Shapiro reports a relationship with Amgen Inc that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Agepha that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Ionis that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Novartis that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Precision Biosciences Inc that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Novo Nordisk Inc that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Regeneron Pharmaceuticals Inc that includes: consulting or advisory. Michael D. Shapiro reports a relationship with EmendoBio Inc that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Aidoc that includes: consulting or advisory. Michael D. Shapiro reports a relationship with Shanghai Pharma Biotherapeutics that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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